Instructions to use Helsinki-NLP/opus-mt-et-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-et-en with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-et-en")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-et-en") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-et-en", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ad069a88c5433161dc0d11cec663f57790b33784117c9e3221a46161aa0b82cb
- Size of remote file:
- 299 MB
- SHA256:
- 6fa6d9110996c42238edb27fdfd3ce5b02b53a441da081f4793a19eb8d0b0012
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